Oligomerization of green fluorescent protein in the secretory pathway of endocrine cells
Bibliographic record
Abstract
Green fluorescent protein (GFP) is used extensively as a reporter protein to monitor cellular processes, including intracellular protein trafficking and secretion. In general, this approach depends on GFP acting as a passive reporter protein. However, it was recently noted that GFP oligomerizes in the secretory pathway of endocrine cells. To characterize this oligomerization and its potential role in GFP transport, cytosolic and secretory forms of enhanced GFP (EGFP) were expressed in GH4C1 and AtT-20 endocrine cells. Biochemical analysis showed that cytosolic EGFP existed as a 27 kDa monomer, whereas secretory forms of EGFP formed disulphide-linked oligomers. EGFP contains two cysteine residues (Cys(49) and Cys(71)), which could play a role in this oligomerization. Site-directed mutagenesis of Cys(49) and Cys(71) showed that both cysteine residues were involved in disulphide interactions. Substitution of either cysteine residue resulted in a reduction or loss of oligomers, although dimers of the secretory form of EGFP remained. Mutation of these residues did not adversely affect the fluorescence of EGFP. EGFP oligomers were stored in secretory granules and secreted by the regulated secretory pathway in endocrine AtT-20 cells. Similarly, the dimeric mutant forms of EGFP were still secreted via the regulated secretory pathway, indicating that the higher-order oligomers were not necessary for sorting in AtT-20 cells. These results suggest that the oligomerization of EGFP must be considered when the protein is used as a reporter molecule in the secretory pathway.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".